Using Classification Models for Diagnostic Factor and Cut-Off Value Discovery

Latvijas Universitātes 73. Zinātniskās konferences Medicīnas sekcijas tēžu apkopojums 2015
Inese Poļaka, Arnis Kiršners, Dace Rudzīte

Commonly various test result data are analysed using statistics methods but they have many shortcomings that point to the need of using different methods that operate with different mathematical parameters. Such approaches in bioinformatics usually consist of data mining methods that are less demanding towards the data and have a good potential in general medical applications to expose hidden knowledge in the data.

Atslēgas vārdi
Data mining
Hipersaite
https://dspace.lu.lv/dspace/bitstream/handle/7/5411/LU-73konference_Medicinas-sekcijas-tezes_2015.pdf?sequence=1

Poļaka, I., Kiršners, A., Rudzīte, D. Using Classification Models for Diagnostic Factor and Cut-Off Value Discovery. No: Latvijas Universitātes 73. Zinātniskās konferences Medicīnas sekcijas tēžu apkopojums, Latvija, Rīga, 20.-20. februāris, 2015. Rīga: ULMA, 2015, 41.-42.lpp.

Publikācijas valoda
English (en)